However, as methods based on prototypes or prior maps have apparent limitations, e.g., disregarding pixel-wise relationships between support and query features por spatial structure of feature maps, numerous recent works [1]}, [2]}, [3]}, [4]}, [5]} attempted to fully utilize a correlation map to leverage the pixel-wise relationships between source and query features. Specifically, [1]}, [2]}, [4]} use graph attention, [3]} proposes efficient 4D convolutions to fully exploit the multi-level features, and [5]} formulates the task as optimal transport problem. However, these approaches either do not provide a means to aggregate the matching scores or lack an ability to consider interactions of matching scores.
